Intelligent Crane Management Algorithm for Construction Operation (iCrane)

Heavy industrial construction project requires the installation of hundreds of large heavy modules. Effective utilization of lifting equipment is critical to ensuring economical project start-up. Capturing and evaluating global crane relocation, movement, and decommissioning, as well as object lift study and digital visualization, is essential in order to reduce costs and time. This paper presents a unique methodology that combines crane selection, optimum lift sequencing, and project global and individual lift visualizations in a single-sequenced algorithm. The state-of-the-art methodology incorporates all site constraints needed to ensure safe, economical crane lifts and proper reactions responsive to site condition changes. The algorithm is divided into several modules and sub-modules which focus on different aspects of the crane management process. The algorithm buildup structure is designed to employ specific volumes or even stage sections independently which allows the user to run either the entire program or just a specific portion. In this paper the authors also discuss modules of site preparation stages of the algorithm and the mechanism for lift object path development. The visualization algorithm presented in this paper is based on specific case studies, and synopsis for such case is provided for further evaluation. A student dormitory at Muhlenberg College in Allentown, Pennsylvania, is presented as a case study demonstrating efficient construction based on advanced equipment planning. 3D visualization-based motion planning is presented to develop motions of mobile crane operation based on various design changes. In the case study, real time construction schedule updating in the weather changes allows the construction site manager to accurately modify crane lift sequence to ensure timely project delivery.